

Ep. 202 Unleashing Vector Search: An Exclusive AMA with Benjamin Flast
Jan 24, 2024
Benjamin Flast, a pivotal member of the MongoDB product team, discusses the intricacies of Vector Search and its relevance to AI and MongoDB. Topics covered include embedding models, benefits over traditional search methods, vector size considerations, Atlas integration, and localization of indexes. The AMA section covers cluster sync, Atlas CLI support, and trade-offs in performance and chunking strategies. The connection to context in language models is explored, as well as the possibility of nesting vector embeddings in MongoDB.
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7
Introduction
00:00 • 2min
Vector Search and its Relevance to AI and MongoDB
01:51 • 16min
AMA with Ben Flast: Cluster Sync and Atlas CLI Support for Vector Search
17:31 • 3min
Localization of Indexes in Atlas Search
20:20 • 3min
Trade-offs in Performance and Chunking Strategies for Vector Searches
22:53 • 3min
Understanding Vector Search and its Connection to Context in Language Models
25:40 • 3min
Nesting Vector Embeddings in MongoDB
28:15 • 19min